Incorporating Problem Based Learning (Pbl) In A Freshman Engineering Course: Methods For Classifying And Assessing Pbl Projects
Author(s) -
Javarro Russell,
Olga Pierrakos,
Megan K. France,
Ronald Kander,
Robin Anderson,
Heather Watson
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--16177
Subject(s) - problem based learning , course (navigation) , computer science , mathematics education , engineering education , project based learning , engineering management , artificial intelligence , engineering , psychology , aerospace engineering
Problem-based learning (PBL), a powerful student-centered pedagogy, offers a strong framework upon which to build a curriculum that will allow students to learn essential problem solving skills. Although PBL methodologies are highly valued, they are not well integrated throughout the engineering education curriculum. This lack of integration stems from unclear classification of the type of projects that constitutes PBL practice. The lack of integration is further diminished by the deficit of assessment studies used to describe the efficacy of the PBL in assisting students in achieving learning outcomes. With a focus on a PBL-based freshman engineering course, in this paper we present: (1) The novel use of a PBL classification framework grounded on dimensions of structuredness, complexity, and team environment. (2) Assessment strategies for analyzing the alignment between the PBL learning experiences and the intended student learning outcomes. (3) The classification and assessment of a freshman PBL project focused on reverse engineering a hand-held mixer. (4) Suggestions on how PBL projects such as the reverse engineering example can be reshaped to meet a span of learning outcomes for engineering students. In summary, what we hope to illustrate in this paper is that structure meets function that is problem structure influences student learning. Novel use of PBL theory on problem classification enables us to capture how the structure of a problem shapes student learning outcomes. The implications of such an effort to utilize a PBL classification framework and assessment methods are that the tools developed herein can be used by engineering programs nationwide, independent of discipline or academic level.
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